Address Resolution Protocol (ARP) spoofing is a critical security threat in wireless networks where an attacker sends forged ARP messages to link their device with the IP address of a legitimate user. This attack allows malicious users to intercept, modify, or block data traffic between communicating devices, leading to serious issues such as data theft, session hijacking, and denial-of-service attacks. Traditional detection mechanisms mainly rely on software-based identifiers such as IP addresses and MAC addresses. However, these identifiers can be easily manipulated by attackers, making conventional solutions less effective in detecting sophisticated attacks. To overcome this limitation, this study proposes a defense mechanism against ARP spoofing in Wi-Fi networks using Radio Frequency (RF) fingerprinting. RF fingerprinting identifies wireless devices based on unique hardware-level characteristics of their transmitted signals. Features such as frequency offset, phase noise, and signal transient patterns are analyzed to generate distinct RF signatures for each device. The proposed system continuously monitors wireless transmissions and compares them with stored RF fingerprints to identify anomalies and detect unauthorized devices. By leveraging physical layer characteristics, the approach provides a reliable and difficult-to-forge method of authentication. Experimental results indicate that RF fingerprinting significantly improves the accuracy of ARP spoofing detection and strengthens overall wireless network security without requiring major modifications to existing infrastructure.